:orphan:



.. _sphx_glr_limo_examples:

.. _general_examples:

Examples Gallery
================

This section of the documentation is learning-oriented and shows off some of the basic functionality of ``MNE-LIMO``.

.. contents:: Contents
   :local:
   :depth: 2


.. raw:: html

    <div style='clear:both'></div>



.. _sphx_glr_limo_examples_single_subject:

Single subject analysis
=======================

This section covers useful analysis techniques that can be used to estimate linear regression effects on a single subject level.



.. raw:: html

    <div class="sphx-glr-thumbcontainer" tooltip="Plot bootstrapped confidence interval for linear model fit">

.. only:: html

    .. figure:: /limo_examples/single_subject/images/thumb/sphx_glr_plot_bootstrap_ci_thumb.png

        :ref:`sphx_glr_limo_examples_single_subject_plot_bootstrap_ci.py`

.. raw:: html

    </div>


.. toctree::
   :hidden:

   /limo_examples/single_subject/plot_bootstrap_ci

.. raw:: html

    <div class="sphx-glr-thumbcontainer" tooltip="Plot beta coefficients from linear model estimation with sklearn">

.. only:: html

    .. figure:: /limo_examples/single_subject/images/thumb/sphx_glr_plot_linear_regression_thumb.png

        :ref:`sphx_glr_limo_examples_single_subject_plot_linear_regression.py`

.. raw:: html

    </div>


.. toctree::
   :hidden:

   /limo_examples/single_subject/plot_linear_regression

.. raw:: html

    <div class="sphx-glr-thumbcontainer" tooltip="References ---------- .. [1] Sander Greenland (2019) Valid P-Values Behave Exactly as They Shou...">

.. only:: html

    .. figure:: /limo_examples/single_subject/images/thumb/sphx_glr_plot_p_values_thumb.png

        :ref:`sphx_glr_limo_examples_single_subject_plot_p_values.py`

.. raw:: html

    </div>


.. toctree::
   :hidden:

   /limo_examples/single_subject/plot_p_values

.. raw:: html

    <div class="sphx-glr-thumbcontainer" tooltip="Plot R">

.. only:: html

    .. figure:: /limo_examples/single_subject/images/thumb/sphx_glr_plot_r_squared_thumb.png

        :ref:`sphx_glr_limo_examples_single_subject_plot_r_squared.py`

.. raw:: html

    </div>


.. toctree::
   :hidden:

   /limo_examples/single_subject/plot_r_squared
.. raw:: html

    <div style='clear:both'></div>



.. _sphx_glr_limo_examples_group_level:

Group-level analysis
====================

This section extends the analysis techniques presented in the single subject analysis section, covering useful tools to estimate linear regression effects on a group level (i.e., including data from multiple subjects).



.. raw:: html

    <div class="sphx-glr-thumbcontainer" tooltip="Plot group">

.. only:: html

    .. figure:: /limo_examples/group_level/images/thumb/sphx_glr_plot_continuous_covariate_thumb.png

        :ref:`sphx_glr_limo_examples_group_level_plot_continuous_covariate.py`

.. raw:: html

    </div>


.. toctree::
   :hidden:

   /limo_examples/group_level/plot_continuous_covariate

.. raw:: html

    <div class="sphx-glr-thumbcontainer" tooltip="Plot group">

.. only:: html

    .. figure:: /limo_examples/group_level/images/thumb/sphx_glr_plot_group_analysis_thumb.png

        :ref:`sphx_glr_limo_examples_group_level_plot_group_analysis.py`

.. raw:: html

    </div>


.. toctree::
   :hidden:

   /limo_examples/group_level/plot_group_analysis

.. raw:: html

    <div class="sphx-glr-thumbcontainer" tooltip="Plot group">

.. only:: html

    .. figure:: /limo_examples/group_level/images/thumb/sphx_glr_plot_group_level_effects_thumb.png

        :ref:`sphx_glr_limo_examples_group_level_plot_group_level_effects.py`

.. raw:: html

    </div>


.. toctree::
   :hidden:

   /limo_examples/group_level/plot_group_level_effects

.. raw:: html

    <div class="sphx-glr-thumbcontainer" tooltip="Plot spatiotemporal clustering results for effect of continuous variable">

.. only:: html

    .. figure:: /limo_examples/group_level/images/thumb/sphx_glr_plot_spatiotemporal_cluster_thumb.png

        :ref:`sphx_glr_limo_examples_group_level_plot_spatiotemporal_cluster.py`

.. raw:: html

    </div>


.. toctree::
   :hidden:

   /limo_examples/group_level/plot_spatiotemporal_cluster

.. raw:: html

    <div class="sphx-glr-thumbcontainer" tooltip="Plot significance t">

.. only:: html

    .. figure:: /limo_examples/group_level/images/thumb/sphx_glr_plot_spatiotemporal_tfce_thumb.png

        :ref:`sphx_glr_limo_examples_group_level_plot_spatiotemporal_tfce.py`

.. raw:: html

    </div>


.. toctree::
   :hidden:

   /limo_examples/group_level/plot_spatiotemporal_tfce
.. raw:: html

    <div style='clear:both'></div>



.. only :: html

 .. container:: sphx-glr-footer
    :class: sphx-glr-footer-gallery


  .. container:: sphx-glr-download

    :download:`Download all examples in Python source code: limo_examples_python.zip <//home/josealanis/Documents/github/mne-stats/sphinx/limo_examples/limo_examples_python.zip>`



  .. container:: sphx-glr-download

    :download:`Download all examples in Jupyter notebooks: limo_examples_jupyter.zip <//home/josealanis/Documents/github/mne-stats/sphinx/limo_examples/limo_examples_jupyter.zip>`


.. only:: html

 .. rst-class:: sphx-glr-signature

    `Gallery generated by Sphinx-Gallery <https://sphinx-gallery.github.io>`_